511-fear-stress-reward

Fun

Fear

Animal models

http://www.cns.nyu.edu/labs/ledouxlab/images/image_research/fear_conditioning.jpg

Adapted from (Davis, 1992)

Amygdala circuits

(Medina, Repa, Mauk, & LeDoux, 2002)

• Direct (fast) pathways via thalamus
• Indirect (slower) pathways via cortex
• Input and output (behavior, physiology) specificity

Specificity of learning stimulus/response mappings

(Pellman & Kim, 2016)

• Specific stimulus/response, \(S \rightarrow R\), patterns
• Visual OR Auditory \(\rightarrow\) pain
• Taste \(\rightarrow\) nausea

Circuitry

(Brandão, Zanoveli, Ruiz-Martinez, Oliveira, & Landeira-Fernandez, 2008)

(Pellman & Kim, 2016)

• BLA, basolateral complex of the amygdala
• CEA, central nucleus of the amygdala
• ITC, intercalated cells of the amygdala
• PL, prelimbic cortex
• IL, infralimbic cortex
• HPC, hippocampus
• Thal, thalamus
• PAG, periaqueductal gray
• PBN, parabrachial nucleus

Stress types

• Acute stress
  • Short duration
• Brain detects threat
• Mobilizes physiological, behavioral responses
  • HPA (Cortisol), SAM (NE/Epi) axes
• vs. Chronic or stress
  • Long duration, persistent

(Kim, Pellman, & Kim, 2015)

Glucocorticoids

• Released by
  • Adrenal cortex
  • Other areas in small amounts
• Cortisol (hydrocortisone)
  • Increases blood glucose levels
  • Aids in fat, protein, carbohydrate metabolism
  • Suppresses immune system
  • Reduces inflammation
• Receptors in body and brain

(Kadmiel & Cidlowski, 2013)

• Multiple feedback loops
• Diurnal pattern

http://www.molecularbrain.com/content/figures/1756-6606-3-2-1-l.jpg

Impacts of chronic stress

• Major depressive disorder (MDD) & Post-traumatic Stress Disorder (PTSD)
  • Hippocampus and PFC volume reductions
  • Synapse loss
  • Reduced dendritic density

(Schmaal et al., 2016)

Cohen’s d-effect sizes 95% CI and for differences in subcortical brain volumes between major depressive disorder (MDD) patients and healthy control subjects. Effect sizes were corrected for age, sex and intracranial volume (ICV). The effect size for ICV was corrected for age and sex. P<0.05 corrected. CI, confidence interval.

(Schmaal et al., 2016)

(a) Cohen’s d-effect sizes 95% CI for differences in subcortical brain volumes between recurrent major depressive disorder (MDD) patients and healthy control subjects (striped pattern) and between first episode MDD patients and healthy controls (no pattern). (b) Cohen’s d-effect sizes 95% CI for differences in subcortical brain volumes between early onset (⩽21) MDD patients and healthy control subjects (no pattern) and between later onset (>21) MDD patients and healthy controls (striped pattern). Effect sizes were corrected for age, sex and intracranial volume (ICV). P<0.05 corrected, P<0.05. CI, confidence interval.

Impacts of acute stress

(Musazzi, Tornese, Sala, & Popoli, 2017)

“Figure 1. Neuroarchitectural Changes Induced by Repeated or Acute Stress in Rodents. (A) Repeated restraint stress (7 days) induces a reduction in the number and length of apical dendrites of pyramidal neurons (layer V) in the medial prefrontal cortex (PFC) of rats. (B) Magnified segment of dendrite from the same stressed rats, showing that repeated stress significantly decreases the number of spine synapses in medial PFC. (C) Reconstructions of representative infralimbic pyramidal neurons in mice exposed to zero (0), one (1×), or three (3×) unpredictable sessions of 10 min of forced swim stress. Apical dendritic branch length was significantly reduced after one or three stress episodes relative to controls. Adapted, with permission, from [24] (B) and [23] (C).”

(Musazzi et al., 2017)

Figure 3. Graphic Summary of Short- and Long-Term Functional and Neuroarchitectural Effects in Prefrontal Cortex (PFC) Synapses after Acute Footshock (FS) Stress [44]. The fast and transient increase in corticosterone (CORT) release induced by acute (40 min) FS stress was accompanied by the rapid increase in both depolarization-evoked and hypertonic sucrose-evoked (readily releasable pool) glutamate release in PFC, and the number of small excitatory synapses. The enhancement of glutamate release was sustained for up to 24 h, as well as the increased number of excitatory synapses, which normalized between 24 h and 7 days after FS. Before 24 h had elapsed from the start of FS stress, retraction of apical dendrites began and was sustained for up to 14 days. The timing of actual FS stress (40 min) is indicated by the red marker. Number of excitatory synapses and apical dendrite length are indicative and not in scale with other readouts. CORT and glutamate release data adapted from [44].

Changes in neural architecture

• Hippocampus (rich in CORT receptors)
• Prefrontal cortex

Neurochemical factors

• Cortisol enhances glutamate release
• Corticosteroid antagonists block this
• Ketamine (NMDA receptor antagonist) may act via similar mechanisms

Sapolsky, Why Zebras Don’t Get Ulcers

Pleasure/reward

From conceptual category to brain circuitry

(Kringelbach & Berridge, 2009)

Figure 1. Measuring reward and hedonia. Reward and pleasure are multifaceted psychological concepts. Major processes within reward (first column) consist of motivation or wanting (white), learning (blue), and – most relevant to happiness – pleasure, liking or affect (light blue). Each of these contains explicit (top rows, light yellow) and implicit (bottom rows, yellow) psychological components (second column) that constantly interact and require careful scientific experimentation to tease apart. Explicit processes are consciously experienced (e.g. explicit pleasure and happiness, desire, or expectation), whereas implicit psychological processes are potentially unconscious in the sense that they can operate at a level not always directly accessible to conscious experience (implicit incentive salience, habits and ‘liking’ reactions), and must be further translated by other mechanisms into subjective feelings. Measurements or behavioral procedures that are especially sensitive markers of each of the processes are listed (third column). Examples of some of the brain regions and neurotransmitters are listed (fourth column), as well as specific examples of measurements (fifth column), such as an example of how highest subjective life satisfaction does not lead to the highest salaries (top) [93]. Another example shows the incentive-sensitization model of addiction and how ‘wanting’ to take drugs may grow over time independently of ‘liking’ and ‘learning’ drug pleasure as an individual becomes an addict (bottom) [94].

Neuroanatomy of ‘pleasure’

(Kringelbach & Berridge, 2009)

Figure 2. Hedonic brain circuitry. The schematic figure shows the brain regions for causing and coding fundamental pleasure in rodents and humans. (a) Facial ‘liking’ and ‘disliking’ expressions elicited by sweet and bitter taste are similar in rodents and human infants. (b, d) Pleasure causation has been identified in rodents as arising from interlinked subcortical hedonic hotspots, such as in nucleus accumbens and ventral pallidum, where neural activation may increase ‘liking’ expressions to sweetness. Similar pleasure coding and incentive salience networks have also been identified in humans. (c) The so-called ‘pleasure’ electrodes in rodents and humans are unlikely to have elicited true pleasure but perhaps only incentive salience or ‘wanting’. (d) The cortical localization of pleasure coding might reach an apex in various regions of the orbitofrontal cortex, which differentiate subjective pleasantness from valence processing for aspects of the same stimulus, such as a pleasant food.

• Analogous circuits mediating facial expressions of “liking” and “disliking”

Reward

• A reward reinforces (makes more prevalent/probable) some behavior
• Milner and Olds (Milner, 1989) discovered ‘rewarding’ power of electrical self-stimulation
• (Heath, 1963) studied effects in human patients.

Electrical self-stimulation

“Reward” circuitry in the brain

(Nestler & Carlezon, 2006)

• Lateral Hypothalamus (Hyp)
• Medial forebrain bundle (MFB)
• Ventral tegmental area (VTA) in midbrain
• Nucleus accumbens (nAcc)
• Dorsal Raphe Nucleus/Locus Coeruleus (DR/LC)
• Amygdala (Amy)
• Hippocampus (HP)
• Prefrontal cortex (PFC)

(Kohls, Chevallier, Troiani, & Schultz, 2012)

What does DA signal?

• Hedonia and anhedonia
• Incentive salience
• Reward prediction error (RPE)

(Hu, 2016)

DA and GABA signaling

(Watabe-Uchida, Eshel, & Uchida, 2017)

Expectation modulates DA signaling

(Watabe-Uchida et al., 2017)

DA network

(Watabe-Uchida et al., 2017)

(Watabe-Uchida et al., 2017)

Reward & Aversion Networks

(Watabe-Uchida et al., 2017)

Psychopharmacology of pleasure

• Dopamine
• Serotonin, Norepinephrine
• ACh

(Cock, Vidailhet, & Arnulf, 2008)

• Opioids, endogenous morphine-like NTs (endorphins)

(Clapp, Bhave, & Hoffman, n.d.)

• Cannabinoids = psychoactive compounds found in cannibis
• Endocannabinoids (endogenous cannabinoid system)
  • Cannabinoid CB1 receptors in CNS; CB2 in body, immune system

(Flores, Maldonado, & Berrendero, 2013)

References

Brandão, M. L., Zanoveli, J. M., Ruiz-Martinez, R. C., Oliveira, L. C., & Landeira-Fernandez, J. (2008). Different patterns of freezing behavior organized in the periaqueductal gray of rats: Association with different types of anxiety. Behavioural Brain Research, 188(1), 1–13. https://doi.org/10.1016/j.bbr.2007.10.018

Clapp, P., Bhave, S. V., & Hoffman, P. L. (n.d.). How Adaptation of the Brain to Alcohol Leads to Dependence. Retrieved from http://pubs.niaaa.nih.gov/publications/arh314/310-339.htm

Cock, V. C. D., Vidailhet, M., & Arnulf, I. (2008). Sleep disturbances in patients with parkinsonism. Nature Clinical Practice Neurology, 4(5), 254–266. https://doi.org/10.1038/ncpneuro0775

Davis, M. (1992). The role of the amygdala in fear-potentiated startle: Implications for animal models of anxiety. Trends in Pharmacological Sciences, 13, 35–41. https://doi.org/10.1016/0165-6147(92)90014-W

Flores, Á., Maldonado, R., & Berrendero, F. (2013). Cannabinoid-hypocretin cross-talk in the central nervous system: What we know so far. Neuropharmacology, 7, 256. https://doi.org/10.3389/fnins.2013.00256

Heath, R. G. (1963). Electrical self-stimulation of the brain in man. American Journal of Psychiatry, 120(6), 571–577. https://doi.org/10.1176/ajp.120.6.571

Hu, H. (2016). Reward and aversion. Annual Review of Neuroscience, 39, 297–324. https://doi.org/10.1146/annurev-neuro-070815-014106

Kadmiel, M., & Cidlowski, J. A. (2013). Glucocorticoid receptor signaling in health and disease. Trends in Pharmacological Sciences, 34(9), 518–530. https://doi.org/10.1016/j.tips.2013.07.003

Kim, E. J., Pellman, B., & Kim, J. J. (2015). Stress effects on the hippocampus: A critical review. Learning & Memory, 22(9), 411–416. https://doi.org/10.1101/lm.037291.114

Kohls, G., Chevallier, C., Troiani, V., & Schultz, R. T. (2012). Social ‘wanting’dysfunction in autism: Neurobiological underpinnings and treatment implications. Journal of Neurodevelopmental Disorders, 4(10), 1–20. https://doi.org/10.1186/1866-1955-4-10

Kringelbach, M. L., & Berridge, K. C. (2009). Towards a functional neuroanatomy of pleasure and happiness. Trends in Cognitive Sciences, 13(11), 479–487.

Medina, J. F., Repa, J. C., Mauk, M. D., & LeDoux, J. E. (2002). Parallels between cerebellum-and amygdala-dependent conditioning. Nature Reviews Neuroscience, 3(2), 122–131. https://doi.org/10.1038/nrn728

Milner, P. M. (1989). The discovery of self-stimulation and other stories. Neuroscience & Biobehavioral Reviews, 13(2–3), 61–67. https://doi.org/10.1016/S0149-7634(89)80013-2

Musazzi, L., Tornese, P., Sala, N., & Popoli, M. (2017). Acute or chronic? A stressful question. Trends in Neurosciences. https://doi.org/10.1016/j.tins.2017.07.002

Nestler, E. J., & Carlezon, W. A. (2006). The mesolimbic dopamine reward circuit in depression. Biological Psychiatry, 59(12), 1151–1159. https://doi.org/10.1016/j.biopsych.2005.09.018

Pellman, B. A., & Kim, J. J. (2016). What can ethobehavioral studies tell us about the brain’s fear system? Trends in Neurosciences, 39(6), 420–431. https://doi.org/10.1016/j.tins.2016.04.001

Schmaal, L., Veltman, D. J., Erp, T. G. M. van, Sämann, P. G., Frodl, T., Jahanshad, N., … Hibar, D. P. (2016). Subcortical brain alterations in major depressive disorder: Findings from the ENIGMA major depressive disorder working group. Molecular Psychiatry, 21(6), 806–812. https://doi.org/10.1038/mp.2015.69

Watabe-Uchida, M., Eshel, N., & Uchida, N. (2017). Neural circuitry of reward prediction error. Annual Review of Neuroscience, 40, 373–394. https://doi.org/10.1146/annurev-neuro-072116-031109